GENECARD-Gene Identification in Early-Onset CAD

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DESCRIPTION (provided by applicant): Coronary artery disease is the single leading cause of death in the US. Coronary Artery disease (CAD) is also a leading cause of disability. Identification of genes increasing susceptibility to CAD would have far reaching public health impact from enhancing motivation to make behavioral and lifestyle changes in susceptible individuals to providing basic biological and clinical information about the development and treatment of CAD. CAD is a complex disease with clear genetic and environmental risk factors. Early onset (premature) coronary artery disease (EOCAD), defined as age of onset less than 50 years of age, is known to have a particularly strong genetic component. However the actual genes leading to this increased risk and to a basic understanding of CAD remain obscure. Our goal is to identify genes increasing susceptibility to early onset coronary disease in a large sample of nuclear families with at least two members with EOCAD defined on the basis of a myocardial infarction, surgical procedure, or functional test before the age of 50 in men or 55 in women. We have completed a genome screen for EOCAD using 395 microsatellite markers in 438 families collected by the GENECARD study, a collaborative study involving 6 clinical investigative sites, GlaxoSmithKline and the Duke Center for Human Genetics. We have identified 9 regions providing consistent evidence for linkage in these families. We will concentrate on a region encompassing chromosome 3q13-q22 providing strong and consistent evidence for linkage (MLS=2.3). We propose to perform follow-up genotyping of microsatellite markers in these regions in the original set of families and in an additional set of almost 400 families. Candidate genes in those regions as well as genes identified from expression analyses carried out in other projects will be analyzed using linkage and family-based association. Our efforts in identifying new markers, SNPs and candidate genes for the follow-up studies will be aided by bioinformatics analyses and tools. We strongly believe that a detailed study of genetic factors and gene-environment interactions is an essential step to identifying targeted preventive strategies and more effective treatments.